DBMS > BoltDB vs. FeatureBase vs. Google BigQuery vs. Oracle Rdb vs. RocksDB

System Properties Comparison BoltDB vs. FeatureBase vs. Google BigQuery vs. Oracle Rdb vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Large scale data warehouse service with append-only tables

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store

Relational DBMS

Key-value store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

github.com/boltdb/bolt

www.featurebase.com

cloud.google.com/bigquery

www.oracle.com/database/technologies/related/rdb.html

rocksdb.org

Technical documentation

docs.featurebase.com

cloud.google.com/bigquery/docs

www.oracle.com/database/technologies/related/rdb-doc.html

github.com/facebook/rocksdb/wiki

Developer

Molecula and Pilosa Open Source Contributors

Google

Oracle, originally developed by Digital Equipment Corporation (DEC)

Facebook, Inc.

Initial release

2013

2017

2010

1984

2013

Current release

2022, May 2022

7.4.1.1, 2021

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
macOS

hosted

HP Open VMS

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL queries

yes

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

Since BigQuery is designed for querying data

yes, on a single node

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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